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  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "830021ee-e20d-416a-86e0-7b6a22aaab14",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "\u001b[?25hInstalling collected packages: namex, libclang, flatbuffers, termcolor, tensorflow-io-gcs-filesystem, tensorboard-data-server, optree, opt-einsum, ml-dtypes, h5py, grpcio, google-pasta, gast, astunparse, absl-py, tensorboard, keras, tensorflow\n",
      "  Attempting uninstall: h5py\n",
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      "    Uninstalling h5py-3.9.0:\n",
      "      Successfully uninstalled h5py-3.9.0\n",
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     ]
    }
   ],
   "source": [
    "!pip install tensorflow\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a8b1eeee-829a-4d4a-b94e-b800e91b36d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np  # For numerical operations\n",
    "import matplotlib.pyplot as plt  # For plotting graphs\n",
    "import wfdb  # For loading and working with PhysioNet data\n",
    "from sklearn.preprocessing import LabelEncoder  # For encoding labels\n",
    "from sklearn.model_selection import train_test_split  # For splitting the data\n",
    "\n",
    "# TensorFlow and Keras for building and training the neural network\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, Flatten\n",
    "\n",
    "# If you haven't installed these libraries yet, you can install them using pip\n",
    "# !pip install numpy matplotlib wfdb scikit-learn tensorflow\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "71641313-8c93-444d-b333-4a4c93a80576",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Signal shape: (650000, 2)\n",
      "Annotation symbols: ['+', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'A', 'N']\n"
     ]
    }
   ],
   "source": [
    "import wfdb\n",
    "\n",
    "# Record name and the PhysioNet database\n",
    "record_name = '100'\n",
    "database_name = 'mitdb'\n",
    "\n",
    "# Load the record from PhysioNet\n",
    "record = wfdb.rdrecord(record_name, pn_dir=database_name)\n",
    "annotation = wfdb.rdann(record_name, 'atr', pn_dir=database_name)\n",
    "\n",
    "# Print the signal and annotation info\n",
    "print(\"Signal shape:\", record.p_signal.shape)\n",
    "print(\"Annotation symbols:\", annotation.symbol[:10])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "683cb542-2acf-4eb6-8999-f1f14fc7eee4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of segments: 2270\n",
      "Example segment shape: (720,)\n"
     ]
    }
   ],
   "source": [
    "def get_segments(signal, annotations, window_size=360):\n",
    "    segments = []\n",
    "    labels = []\n",
    "    for idx, symbol in enumerate(annotations.symbol):\n",
    "        center = annotations.sample[idx]\n",
    "        if center < window_size or center > signal.shape[0] - window_size:\n",
    "            continue  # Skip beats too close to the start or end\n",
    "        segment = signal[center-window_size:center+window_size]\n",
    "        segments.append(segment)\n",
    "        labels.append(symbol)\n",
    "    return np.array(segments), np.array(labels)\n",
    "\n",
    "# Get segments and labels\n",
    "segments, labels = get_segments(record.p_signal[:,0], annotation)  # Using only channel 1 for simplicity\n",
    "\n",
    "print(\"Number of segments:\", len(segments))\n",
    "print(\"Example segment shape:\", segments[0].shape)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "835e9dac-b707-4f3d-b25b-cb84b57450e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Encoded labels example: [1 1 1 1 1 1 0 1 1 1]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "# Initialize the encoder\n",
    "le = LabelEncoder()\n",
    "\n",
    "# Fit and transform the labels to encode them\n",
    "encoded_labels = le.fit_transform(labels)\n",
    "\n",
    "# Check the first few encoded labels\n",
    "print(\"Encoded labels example:\", encoded_labels[:10])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5abe4121-d29a-43bf-9a73-6ea2ebd53ae1",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "# Assuming 'segments' and 'labels' are already defined\n",
    "le = LabelEncoder()\n",
    "encoded_labels = le.fit_transform(labels)\n",
    "\n",
    "# Split the data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(segments, encoded_labels, test_size=0.2, random_state=42)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bbdb0681-e79b-4360-8d7c-31c1034d7936",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_1\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_1\"\u001b[0m\n"
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     "metadata": {},
     "output_type": "display_data"
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     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ flatten_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">720</span>)            │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)            │        <span style=\"color: #00af00; text-decoration-color: #00af00\">92,288</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">8,256</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">3</span>)              │           <span style=\"color: #00af00; text-decoration-color: #00af00\">195</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ flatten_1 (\u001b[38;5;33mFlatten\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m720\u001b[0m)            │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_3 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m)            │        \u001b[38;5;34m92,288\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_4 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m)             │         \u001b[38;5;34m8,256\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_5 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m3\u001b[0m)              │           \u001b[38;5;34m195\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">100,739</span> (393.51 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m100,739\u001b[0m (393.51 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">100,739</span> (393.51 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m100,739\u001b[0m (393.51 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from tensorflow.keras.layers import Input\n",
    "\n",
    "# Define the neural network structure with an Input layer\n",
    "model = Sequential([\n",
    "    Input(shape=(720,)),  # Explicitly define the input shape here\n",
    "    Flatten(),            # Now Flatten doesn't need the input_shape\n",
    "    Dense(128, activation='relu'),  # First dense layer\n",
    "    Dense(64, activation='relu'),   # Second dense layer\n",
    "    Dense(len(set(encoded_labels)), activation='softmax')  # Output layer with one neuron per class\n",
    "])\n",
    "\n",
    "# Compile the model\n",
    "model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])\n",
    "\n",
    "# Show the model summary to understand the architecture\n",
    "model.summary()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "fffcec11-056a-4596-a6c2-50811d025fb7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 3ms/step - accuracy: 0.9595 - loss: 0.2006 - val_accuracy: 0.9890 - val_loss: 0.0635\n",
      "Epoch 2/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9828 - loss: 0.0760 - val_accuracy: 0.9890 - val_loss: 0.0429\n",
      "Epoch 3/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9862 - loss: 0.0363 - val_accuracy: 0.9890 - val_loss: 0.0212\n",
      "Epoch 4/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9939 - loss: 0.0168 - val_accuracy: 1.0000 - val_loss: 0.0177\n",
      "Epoch 5/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9986 - loss: 0.0068 - val_accuracy: 1.0000 - val_loss: 0.0027\n",
      "Epoch 6/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 0.9999 - loss: 0.0026 - val_accuracy: 1.0000 - val_loss: 0.0024\n",
      "Epoch 7/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 0.0025 - val_accuracy: 1.0000 - val_loss: 8.8488e-04\n",
      "Epoch 8/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 7.9515e-04 - val_accuracy: 1.0000 - val_loss: 8.2847e-04\n",
      "Epoch 9/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 5.3443e-04 - val_accuracy: 1.0000 - val_loss: 4.0734e-04\n",
      "Epoch 10/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 4.9236e-04 - val_accuracy: 1.0000 - val_loss: 3.2037e-04\n",
      "Epoch 11/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 3.3084e-04 - val_accuracy: 1.0000 - val_loss: 2.6903e-04\n",
      "Epoch 12/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 2.8925e-04 - val_accuracy: 1.0000 - val_loss: 2.1728e-04\n",
      "Epoch 13/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 2.8131e-04 - val_accuracy: 1.0000 - val_loss: 1.7854e-04\n",
      "Epoch 14/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 3.8260e-04 - val_accuracy: 1.0000 - val_loss: 1.4993e-04\n",
      "Epoch 15/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 1.8087e-04 - val_accuracy: 1.0000 - val_loss: 1.3786e-04\n",
      "Epoch 16/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 1.6856e-04 - val_accuracy: 1.0000 - val_loss: 1.1641e-04\n",
      "Epoch 17/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 1.1262e-04 - val_accuracy: 1.0000 - val_loss: 1.0665e-04\n",
      "Epoch 18/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 1.1942e-04 - val_accuracy: 1.0000 - val_loss: 1.0787e-04\n",
      "Epoch 19/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 1.0361e-04 - val_accuracy: 1.0000 - val_loss: 7.5947e-05\n",
      "Epoch 20/20\n",
      "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step - accuracy: 1.0000 - loss: 8.5026e-05 - val_accuracy: 1.0000 - val_loss: 6.8077e-05\n"
     ]
    }
   ],
   "source": [
    "# Train the model\n",
    "history = model.fit(X_train, y_train, epochs=20, validation_split=0.1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5ebe2db8-266b-4783-9d93-0c53b0f9d262",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m15/15\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 682us/step - accuracy: 0.9984 - loss: 0.0023   \n",
      "Test accuracy: 99.78%\n",
      "Test loss: 0.003153\n"
     ]
    }
   ],
   "source": [
    "test_loss, test_accuracy = model.evaluate(X_test, y_test)\n",
    "print(f\"Test accuracy: {test_accuracy * 100:.2f}%\")\n",
    "print(f\"Test loss: {test_loss:.6f}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "108320fa-338a-48b5-b076-ed5cdf104b19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 4))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.plot(history.history['accuracy'], label='Training Accuracy')\n",
    "plt.plot(history.history['val_accuracy'], label='Validation Accuracy')\n",
    "plt.title('Model Accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.legend(loc='lower right')\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.plot(history.history['loss'], label='Training Loss')\n",
    "plt.plot(history.history['val_loss'], label='Validation Loss')\n",
    "plt.title('Model Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.legend(loc='upper right')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e9ae2acd-4122-43b1-a5d8-fbc1482a9940",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m15/15\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       1.00      0.83      0.91         6\n",
      "           1       1.00      1.00      1.00       448\n",
      "\n",
      "    accuracy                           1.00       454\n",
      "   macro avg       1.00      0.92      0.95       454\n",
      "weighted avg       1.00      1.00      1.00       454\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix, classification_report\n",
    "import seaborn as sns\n",
    "\n",
    "# Predictions\n",
    "y_pred = model.predict(X_test)\n",
    "y_pred_classes = np.argmax(y_pred, axis=1)\n",
    "\n",
    "# Confusion Matrix\n",
    "cm = confusion_matrix(y_test, y_pred_classes)\n",
    "plt.figure(figsize=(10, 7))\n",
    "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues')\n",
    "plt.xlabel('Predicted Labels')\n",
    "plt.ylabel('True Labels')\n",
    "plt.title('Confusion Matrix')\n",
    "plt.show()\n",
    "\n",
    "# Classification Report\n",
    "print(classification_report(y_test, y_pred_classes))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8f68fc8d-0c97-4386-84cc-ea6fd93663a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m15/15\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 677us/step\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.11/site-packages/sklearn/metrics/_ranking.py:1029: UndefinedMetricWarning: No positive samples in y_true, true positive value should be meaningless\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve, auc\n",
    "from sklearn.preprocessing import label_binarize\n",
    "\n",
    "# Binarize labels for multi-class ROC\n",
    "y_test_bin = label_binarize(y_test, classes=np.unique(y_train))\n",
    "y_pred_bin = model.predict(X_test)  # Get probabilities instead of predicted labels\n",
    "\n",
    "# Compute ROC curve and ROC area for each class\n",
    "fpr = dict()\n",
    "tpr = dict()\n",
    "roc_auc = dict()\n",
    "n_classes = y_test_bin.shape[1]\n",
    "\n",
    "for i in range(n_classes):\n",
    "    fpr[i], tpr[i], _ = roc_curve(y_test_bin[:, i], y_pred_bin[:, i])\n",
    "    roc_auc[i] = auc(fpr[i], tpr[i])\n",
    "\n",
    "# Plot ROC curve for a specific class\n",
    "for i in range(n_classes):\n",
    "    plt.figure()\n",
    "    plt.plot(fpr[i], tpr[i], label='ROC curve (area = %0.2f)' % roc_auc[i])\n",
    "    plt.plot([0, 1], [0, 1], 'k--')\n",
    "    plt.xlim([0.0, 1.0])\n",
    "    plt.ylim([0.0, 1.05])\n",
    "    plt.xlabel('False Positive Rate')\n",
    "    plt.ylabel('True Positive Rate')\n",
    "    plt.title('Receiver Operating Characteristic for class %s' % le.classes_[i])\n",
    "    plt.legend(loc=\"lower right\")\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3c49e0bd-d92d-4c0f-8dd3-f920cf1faef1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_ecg_with_annotation(index):\n",
    "    plt.figure(figsize=(14, 5))\n",
    "    plt.plot(X_test[index], label=f\"Predicted: {le.inverse_transform([y_pred_classes[index]])[0]}, True: {le.inverse_transform([y_test[index]])[0]}\")\n",
    "    plt.title('ECG Signal with Model Prediction')\n",
    "    plt.xlabel('Samples')\n",
    "    plt.ylabel('Amplitude')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "# Plot for a specific index\n",
    "plot_ecg_with_annotation(10)  # Change index as needed\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "882c04a1-c38a-4c08-abc0-e8dfcd5d8a68",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
